A new integrated architecture for distributed planning and scheduling is proposed that exploits constraints for problem decomposition and coordination. The goal is to develop an efficient method to solve densely constrained planning/scheduling problems in a distributed manner without sacrificing solution quality. A prototype system (CAMPS) was implemented, in which a set of intelligent agents try to coordinate their actions for ‘satisfying’ planning/scheduling results by handling several intra- and inter-agent constraints. The repair-based methodology for distributed planning/scheduling is described, together with the constraint-based mechanism of dynamic coalition formation among agents.